fix comment

Author: iamrk04

articles/machine-learning/how-to-automl-forecasting-faq.md

@@ -142,25 +142,25 @@ If your AutoML forecasting job fails, you'll see an error message in the studio
 
 Model from forecasting training jobs can be deployed in either of the two ways:
 
-1. Online Endpoint
+- Online Endpoint
     - Please refer [this link](./how-to-deploy-automl-endpoint.md) for online deployment.
     - You can check the scoring file used in the deployment or click on the "Test" tab on the endpoint page in the studio to understand the structure of input that is expected by the deployment.
     - You can refer [this notebook](https://github.com/Azure/azureml-examples/blob/main/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand/automl-forecasting-task-energy-demand-advanced-mlflow.ipynb) to see an example.
-2. Batch Endpoint
+- Batch Endpoint
     - Please refer [this link](./how-to-use-batch-endpoint.md) for batch deployment.
     - It requires you to develop a custom scoring script.
     - You can refer [this notebook](https://github.com/Azure/azureml-examples/blob/main/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales/automl-forecasting-orange-juice-sales-mlflow.ipynb) to see an example.
 
 For UI deployments, we encourage to use either of the two options:
-1. Real-time endpoint
-2. Batch endpoint
+- Real-time endpoint
+- Batch endpoint
 
-:::image type="content" source="media/how-to-automl-forecasting-faq/deployment_UI.png" alt-text="A view of the possible deployment options for an AutoML forecasting model.":::
+:::image type="content" source="media/how-to-automl-forecasting-faq/deployment-ui.png" alt-text="A view of the possible deployment options for an AutoML forecasting model.":::
 
 **Please don't use the 1st option i.e. "Real-time-endpoint (quick)"**.
 
 > [!NOTE]
-> As of now, we don't support deploying MLflow model from forecasting training jobs through SDK, CLI, or UI. You will run into errors if you try this. This feature will be available very soon.
+> As of now, we don't support deploying MLflow model from forecasting training jobs through SDK, CLI, or UI. You will run into errors if you try this.
 
 ## What is a workspace / environment / experiment/ compute instance / compute target?